An inexact inferencing strategy for spatial objects with determined and indeterminate boundaries

Advances in type-2 fuzzy sets and systems

“…Approximation: [61] (TSK/steel strip temperature); Clustering: [26] (C spherical shells algorithm), [72] (fuzzy C-means); Control: [40] (marine and traction diesel engines), [75] (integrated development platform), [4] (evolutionary computing/NL dynamic plants), [36] (buck DC-DC converters), [17] (tracking mobile objects/robotic soccer games), [93] (liquid-level), [81] (proportional control), [25] (autonomous mobile robots), [24] (autonomous mobile robots/hierarchical), [44] (adaptive control of nonlinear plants); Databases: [67] (summarization); Decision making: [70] (variation in human decision making); Embedded agents: [10,11] (ambient intelligent environments); Health care: [27] (clinical diagnosis), [9] (differential diagnosis), [92] (nursing assessment); Hidden Markov models: [103] (phoneme recognition); Neural networks: [73] (fuzzy perceptron); Noise cancellation: [3] (adaptive noise cancellation); Pattern classification: [74] (fuzzy k-nearest neighbor); Quality Control: [45] (sound speakers); Spatial query: [71] (spatial objects); Wireless communications: [35] (wireless sensors/power on-off control), [77] (wireless sensor network lifetime analysis).…”